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Multistate mark-recapture model selection using score tests

McCrea, Rachel S., Morgan, Byron J. T. (2011) Multistate mark-recapture model selection using score tests. Biometrics, 67 (1). pp. 234-241. ISSN 0006-341X. (doi:10.1111/j.1541-0420.2010.01421.x) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1111/j.1541-0420.2010.01421.x

Abstract

Although multistate mark-recapture models are recognized as important, they lack a simple model-selection procedure. This article proposes and evaluates a step-up approach to select appropriate models for multistate mark-recapture data using score tests. Only models supported by the data require fitting, so that over-complicated model structures with too many parameters do not need to be considered. Typically only a small number of models are fitted, and the procedure is also able to identify parameter-redundant and near-redundant models. The good performance of the technique is demonstrated using simulation, and the approach is illustrated on a three-region Canada goose data set. In this case, it identifies a new model that is much simpler than the best model previously considered for this application.

Item Type: Article
DOI/Identification number: 10.1111/j.1541-0420.2010.01421.x
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Faculties > Sciences > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Rachel McCrea
Date Deposited: 29 Jun 2011 16:41 UTC
Last Modified: 01 Aug 2019 10:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/27602 (The current URI for this page, for reference purposes)
McCrea, Rachel S.: https://orcid.org/0000-0002-3813-5328
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